Corporate entities typically collect, manage, and review massive amounts of information electronically on a daily basis. Such information is comprised of structured, numerical data, and unstructured text documents, wherein separate data entry forms often require duplicate information within their fields, such as “customer name,” “customer number,” “customer address,” and so forth.
These processes are usually cumbersome and error-prone due to manual updates to related data and documents. The high error rates are caused by missing or wrong key information (e.g., customer number). In addition, there may be data inconsistencies. For example, a customer's name may not match the customer's assigned number.
These processes also tend to be user-unfriendly, hampering workflow and decision making due to their lack of integrating textual and numerical information. They further lack in efficiency, since duplicate information fields are entered and re-entered manually. Re-keying of certain data, such as customer number or contract number, in an order entry or contract management application, presents another set of issues, namely reduced productivity and increased possibility of data entry errors.
Furthermore, these processes are inflexible in handling data changes during the information gathering stage. A minimal change, for instance, to the “customer name” may induce a series of changes everywhere the “customer name” field appears in the document, requiring modifications of yet other relational documents.
It would therefore be desirable to have a system that addresses and resolves these concerns.